Wireless localisation system

ABSTRACT

Disclosed is method of computing a round trip delay between a pair of nodes, the method comprising transmitting at least one beacon at a known transmit time from each of the nodes; measuring the times-of-arrival of the beacons at other of the nodes; and estimating a round trip delay between the nodes from the measured times-of-arrival and the transmit times; and correcting the round trip delay for either or both of a frequency offset between the nodes and relative motion between the nodes.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/225,011, filed Sep. 1, 2016, which is a continuation of U.S. patentapplication Ser. No. 13/002,640, filed Mar. 23, 2011, which is a U.S.National Stage of International Application No. PCT/AU2009/000863, filedJul. 3, 2009, which claims priority to Australian ProvisionalApplication No. 2008903441, filed Jul. 4, 2008, the entire disclosuresof which are incorporated by reference herein.

FIELD OF THE INVENTION

The present invention relates generally to wireless localisation, and inparticular to tracking objects using radio signals based on measurementof the time-of-arrival.

BACKGROUND

There are many applications in which it is desirable to track or locateobjects or people, such as: tracking athletes for training or providingevent information in real time; tracking emergency services or militarypersonnel in buildings and urban environments; tracking staff, patients,and equipment in hospitals and nursing homes; and tracking staff andequipment in industrial, hazardous or mining environments for safety andautomation.

A wireless localisation system refers to any system that usestransmission of electromagnetic signals (e.g. radio frequency ormicrowave) to localise (estimate the location of) an object, in twodimensions or three dimensions. Mobile objects can be localised and/ortracked by attaching a signal-enabled tag to the object and using a setof fixed ‘anchor’ nodes in the area to be monitored. Inaccuracies in thelocation estimates arise due to (1) the properties of the radiopropagation environment (e.g. multipath reflections and diffraction) and(2) limitations in the system hardware (e.g. lack of time/frequencysynchronisation and propagation delays in hardware that are timevarying). The latter issues are particularly severe in applicationswhere the anchor nodes have wireless connections and must consist oflow-cost hardware.

There are numerous systems for wireless localisation of objects orpeople. Optical, infra-red and ultrasonic localisation do not workthrough walls. Amongst radio localisation systems, the varioustechniques rely on measurement of received signal strength (RSS),time-of-arrival (TOA), and/or angle-of-arrival (AOA). It is well knownthat in difficult radio propagation environments, RSS techniques havepoor accuracy. AOA techniques require expensive hardware to determinethe direction of arrival, and may perform poorly in multipathenvironments where reflections arrive from many directions. A commonTOA-based technique is satellite navigation (e.g. GPS); however, this isnot possible in indoor environments or even in outdoor environmentswhere the accuracy is significantly degraded by multipath signals (e.g.urban canyons).

The most common TOA-based localisation system uses receiving anchornodes that are hard-wired (cabled) to the processing hardware (e.g. U.S.Pat. No. 6,831,603). This greatly simplifies the system as a commonclock can be shared, eliminating the problem of frequency and timesynchronisation. In some situations, such as where rapid installation isrequired or the region between receiving nodes is inaccessible orinappropriate for cable installation, cabled connections between anchornodes are impractical.

Where there is wireless connection between anchor nodes, the frequencyand time synchronisation problem is often handled by using two way (alsoknown as round trip) localisation, and usually also by the use of areference node (e.g. US Patent 2003/0092448). This approach transmits asignal from one node to another, followed immediately by a returnsignal. The time between receiving the forward message and transmittingthe reverse message is often assumed to be constant, which is not thecase in many practical systems.

Once the distance or ‘range’ between each mobile node and the anchornodes has been determined, the location of the mobile nodes is estimatedin a process known as ‘multilateration’. The most common technique usesa minimum mean squared error (MMSE) approach. With this technique, ‘bad’range data can severely affect the estimated locations of the mobilenodes. Another technique with a different assumption on the errordistribution is based on Projections onto Convex Sets (POCS); however,conventional POCS algorithms do not handle well the case where there isa large intersection region. As with MMSE, the POCS approach issusceptible to bad data due to effects such as multipath reflections,radio interference and fading phenomena.

SUMMARY

It is an object of the present invention to substantially overcome, orat least ameliorate, one or more disadvantages of existing arrangements.

According to a first aspect of the present disclosure, there is provideda method of computing a round trip delay between a pair of nodes, themethod comprising:

transmitting at least one beacon at a known transmit time from each ofsaid nodes;

measuring the times-of-arrival of said beacons at other of said nodes;

estimating a round trip delay between said nodes from said measuredtimes-of-arrival and said transmit times; and

correcting said round trip delay for either or both of a frequencyoffset between the nodes and relative motion between the nodes.

According to another aspect of the present disclosure, there is provideda method of estimating the location of a mobile object using a pluralityof ranges between a node associated with said object and respectiveanchor nodes, the method comprising:

estimating, for a current said range, the location of said object and anerror in said location estimate from said range excluding said currentrange;

discarding the range whose exclusion gave the lowest error estimate, ifsaid lowest error estimate is less than a threshold;

repeating said estimating and said discarding until said lowest errorestimate is not less than said threshold or the number of undiscardedranges reaches a minimum number;

and estimating the location of said object from the undiscarded ranges.

According to another aspect of the present disclosure, there is provideda method of estimating the location of a mobile object using a pluralityof ranges between a node associated with said object and respectiveanchor nodes, the method comprising:

projecting a starting point onto a sequence of constraint sets in turn,each said constraint set being a circle centred on one said anchor nodewith radius equal to the corresponding range, to obtain an end point;

increasing, if said end point is not less than said corresponding rangefrom each said anchor node, at least one said range, and

repeating said projecting and said increasing until said location isless than said corresponding range from each said anchor node,

wherein said end point is said estimated location of said mobile object.

According to another aspect of the present disclosure, there is provideda method of time synchronising a plurality of anchor nodes, the methodcomprising:

measuring a plurality of trip delays of beacons transmitted between saidanchor nodes;

correcting said trip delays for propagation delays at said anchor nodesand frequency offsets between local clocks at respective said anchornodes; and

determining a time offset of each said local clock from said correctedtrip delays.

According to another aspect of the present disclosure, there is provideda method of estimating the location of a mobile object using a pluralityof anchor nodes, the method comprising:

synchronising said plurality of anchor nodes;

measuring a plurality of times-of-arrival of beacons transmitted fromsaid object to respective said anchor nodes; and

estimating the location of said object relative to said anchor nodesusing said measured times-of-arrival, corrected for a propagation delayat each said anchor node.

According to another aspect of the present disclosure, there is provideda system for estimating the location of one or more objects, the systemcomprising:

a plurality of anchor nodes;

one or more mobile nodes coincident with respective said objects;

beacons transmitted by some or all of said nodes according to apredetermined or dynamically determined schedule; and

data capability to send measured times-of-arrival of said beacons, andtransmit times of said beacons, to a location server adapted to computethe location of said objects.

According to another aspect of the present disclosure, there is provideda system for estimating the location of an object, the systemcomprising:

a plurality of anchor nodes adapted to communicate wirelessly with eachother by either transmitting or receiving beacons;

a mobile node coincident with said object, the mobile node being adaptedto communicate wirelessly with said anchor nodes by either transmittingor receiving said beacons;

a localisation server adapted to:

-   -   receive measurements of time-of-arrival of said beacons at said        nodes,    -   select one of a plurality of localisation algorithms dependent        on attributes of said anchor nodes and said mobile node, and

estimate the location of said object using said measuredtimes-of-arrival using said selected localisation algorithm.

The disclosed arrangements include a system for wireless localisationand tracking, and methods that can be used in the disclosed system orother systems. The disclosed arrangements estimate object location usingmultilateration based on measured time-of-arrival (TOA) of radiosignals. The disclosed arrangements enable more robust processing andhence more accurate location estimation compared to existing systems andmethods in the face of bad data due to typical sources of error such asTOA measurement errors (e.g. due to multipath interference orpropagation effects), unsynchronised clocks in nodes, time varyingpropagation delay through the node electronics, and object motion. Thedisclosed system, using only low-cost consumer electronic components, iscapable of covering large areas (i.e. is not limited to direct radiocommunication links between all nodes) and is capable of rapiddeployment as cabling is not required between any nodes.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more embodiments of the present invention will now be describedwith reference to the drawings and appendices, in which:

FIG. 1 shows an example of a tracking system within which the disclosedarrangements may be practised;

FIG. 2 is a flow diagram illustrating a general method of localisationaccording to the preferred embodiment;

FIG. 3 is a schematic block diagram of a general purpose computer uponwhich disclosed methods can be practised;

FIG. 4a is an illustration of a beaconing node according to thepreferred embodiment;

FIG. 4b is an illustration of the format of a beacon according to thepreferred embodiment;

FIG. 5 is an illustration of an exemplary TDMA beacon schedule;

FIG. 6 is an illustration of a location server according to thepreferred embodiment;

FIG. 7 is a flow diagram illustrating a method of estimating thelocation of mobile nodes according to the preferred embodiment;

FIG. 8a illustrates a sequence of beacon transmissions;

FIG. 8b illustrates the motion of a mobile node during the beacontransmissions of FIG. 8 a;

FIG. 9 illustrates the estimation of the location of a node according tothe POCS algorithm in an example scenario; and

Appendix A contains pseudocode for a robust MMSE algorithm forestimating the location of a mobile node.

DETAILED DESCRIPTION INCLUDING BEST MODE

Where reference is made in any one or more of the accompanying drawingsto steps and/or features, which have the same reference numerals, thosesteps and/or features have for the purposes of this description the samefunction(s) or operation(s), unless the contrary intention appears.

One application for wireless tracking is in sports such as soccer. FIG.1 shows an example of a tracking system 100 within which the disclosedarrangements may be practised, comprising one soccer player 110, severalfixed anchor nodes, e.g. 120, surrounding the field, and a locationserver 130. Through the exchange of radio signals between the player 110and the anchor nodes 120, and the exchange of data between the anchornodes 120 and the location server 130, it is possible for the locationof the player 110 to be estimated at the location server 130. A keyfeature of the system 100 is that the anchor nodes 120 are wirelesslyconnected to the location server to simplify deployment (although whereconvenient a cable or fibre connection can be used and will usuallyimprove system performance).

There are many other applications for such a system, including trackingand communicating with emergency services personnel and hospital staffand patients. Although the present disclosure refers to a single hopnetwork as shown in FIG. 1, the disclosed arrangements are readilyextendable to other network topologies including multi-hop and mesh.

The disclosed tracking system comprises:

-   -   Mobile Nodes (or tags): These are devices attached to the        objects to be tracked. A mobile node contains a radio        transceiver and computational resources, and optionally sensors        or other sinks or sources of data.    -   Anchor Nodes: These are devices scattered through the area being        monitored at known locations, and communicate wirelessly with        mobile nodes and other anchor nodes. Each anchor node contains a        radio transceiver and computational resources, and optionally        sensors or other sinks or sources of data.    -   Location Server: This is where the locations of the mobile nodes        are estimated using data measured and transmitted by the nodes.        The location estimates and other data are made available to        other systems not described herein. The location server is        preferably a separate physical entity from the anchor nodes, but        need not be, and the estimation computations could be performed        in one of the anchor nodes, or even be distributed over multiple        anchor nodes.

The wireless data communication is preferably performed using directsequence spread spectrum signalling; however, it could be equally wellperformed using any radio communication protocol (e.g. the 802.11 familyof standards).

FIG. 2 is a flow diagram illustrating a general method 200 oflocalisation according to the preferred embodiment. In step 210 certainnodes called beaconing nodes periodically transmit radio signals calledbeacons that are received by some other nodes called TOA reception nodesthat are able to measure the TOA of the beacon. The beacons contain alocalisation signal designed for accurate measurement of TOA and anoptional data payload. While the localisation signal could be a datasymbol, better results are obtained using a specially designedlocalisation signal. Depending upon the application, the hardwarecapability, and the choice of localisation algorithm, the mobile nodesmay be beaconing nodes and/or TOA reception nodes, and likewise theanchor nodes may be beaconing nodes and/or TOA reception nodes. Forexample:

-   -   for tracking, the mobile nodes are beaconing nodes and the        anchor nodes are TOA reception nodes;    -   for navigation, in which the mobile nodes need to estimate their        own location, the mobile nodes are TOA reception nodes and the        anchor nodes are beaconing nodes (this is similar to GPS);    -   for round trip localisation, both anchor nodes and mobile nodes        are both beaconing nodes and TOA reception nodes.

In the disclosed arrangements, a TDMA (time division multiple access)scheme is used for the transmission of the beacons such that only onebeacon is sent in each time slot. TDMA is superior to CDMA (codedivision multiple access) or FDMA (frequency division multiple access)as the former reduces the signal to noise ratio (SNR) at the receiversdue to multiple simultaneous transmissions, reducing localisationaccuracy, and the latter reduces bandwidth available for thelocalisation signal, again reducing localisation accuracy.

At step 220 of the method 200, the TOA reception nodes measure the TOAfor each received beacon, and at step 230 the TOA reception nodes sendthe TOA data to the location server (preferably via the data payload intheir own beacons, or alternatively via other means such as cable,particularly if a TOA reception node is not also a beaconing node). Forsome localisation algorithms, the transmit time of beacons is alsorequired, and beaconing nodes can send this to the location server as adata field in the beacon or by other means. There may be other data suchas that related to system operation, for protocols, or from sensors,that is also sent to the location server. The location server at step240 applies a localisation algorithm to the received data to estimatethe location of the mobile nodes.

There are three main categories of localisation algorithm:

-   -   Round Trip Localisation: Based on bidirectional beacon        transmission between pairs of nodes (mobile and anchor):        eliminates the requirement for time synchronisation, but        requires both mobile and anchor nodes to be both beaconing and        TOA reception nodes.    -   Mobile Transmit Localisation: Localisation is based on a single        beacon transmission by a mobile node, and mobile nodes can be        simpler than for round trip localisation as they only need to be        beaconing nodes. Mobile nodes do not measure TOA, but still need        to have a receiver for TDMA synchronisation. Anchor nodes only        need to be TOA reception nodes for localisation, but will        preferably also be beaconing nodes for time synchronisation        amongst themselves and possibly measurement of their propagation        delay.    -   Mobile Receive Localisation: As with GPS, it is possible for the        anchor nodes to be beaconing nodes and the mobile nodes to be        TOA reception nodes. This category is generally inferior to the        previous two localisation algorithm categories, so will not be        further described below.

When using wireless localisation and tracking, there are a number offactors that adversely affect the accuracy of the estimation of thelocation of the mobile nodes, some of which are only relevant forparticular localisation algorithms or circumstances:

-   -   Errors in the measured TOA can arise due to noise, propagation        effects, interference or signal processing artefacts.    -   Each node has a local clock, and in general the node clocks are        not time or frequency synchronised. Time synchronisation is not        required for round trip localisation, but correction for        frequency offset is still required.    -   There is a propagation delay of radio signals through the        electronics at both the transmitter and receiver nodes. This can        be larger than the propagation delay of the radio signals over        the air between nodes and must be corrected for.    -   A mobile node may be in motion during the localisation        measurement. As discussed below, this is particularly relevant        for round trip localisation.

A beaconing node 400 according to the preferred embodiment isillustrated in FIG. 4a . The beaconing node 400 has digital electronics430 to generate a beacon and a module 420 to convert the beacon toanalog form for radio transmission using a radio transceiver 410 in step210 of the method 200. The beaconing node 400 also receives data atleast to allow synchronisation of TDMA slots, so the data flow in thebeaconing node 400 is bidirectional.

The format of a beacon 450 according to the preferred embodiment,comprising a header 460, a data field (payload) 470, and a TOAlocalisation signal 480, is illustrated in FIG. 4b . The TOAlocalisation signal 480 is specially designed to maximise the accuracywith which the TOA of the signal is measured by a TOA reception node. Inanother embodiment, a separate TOA localisation signal 480 is not usedand instead a known signal pattern in the header 460 is used to measurethe TOA. The data field 470 is optional.

In the preferred embodiment, the beacons 450 are scheduled to minimiseself-interference and hence maximise localisation accuracy. The updaterate of a mobile node's location estimate is limited to the rate atwhich that node transmits beacons.

Previous schemes for round trip localisation involved a beacon beingsent to a node and a reply being immediately generated. For all nodesinvolved in the measurement (for time synchronisation, propagation delaymeasurement or mobile node localisation), there is a beacon sent fromeach node to each of the other nodes. By contrast, according to thedisclosed arrangements for round trip localisation, each beaconing nodetransmits just one beacon per measurement. The advantage is that thenumber of localisation signal transmissions is greatly reduced, whichcan reduce power consumption and/or increase the number of nodes thesystem can support. Under the disclosed arrangements, there can be largeand variable time intervals between the transmissions of beacons betweenpairs of nodes. As described in detail below, this time interval ismeasured and adequately corrected for.

The preferred TDMA scheme 500, with an exemplary schedule, isillustrated in FIG. 5. Time is divided into slots, e.g. 510, with abeacon being sent in each slot by the node corresponding to the slotlabel (M1 is mobile node 1, A1 is anchor node 1, etc). Where the nodesare distributed over a sufficiently large area to form a multi-hopnetwork, a slot can be used by plural nodes, provided the minimum radiolink hop count between the nodes using the same slot is greater than two(hence not all nodes have the same schedule). The slot size willgenerally be as small as possible, preferably adjustable between 1 msand 10 ms. The update rate of the beacons is determined by thelocalisation algorithm category. For round trip localisation, all nodesshould transmit at least at the minimum localisation update rate. Formobile transmit localisation, the mobile nodes should transmit at theminimum localisation update rate; however the anchor nodes shouldtransmit at the required rate to maintain time synchronisation, which isin turn dependent upon the stability of the local oscillators in eachnode.

In FIG. 5, the slots are grouped in superframes, e.g. 520, as thissimplifies the TDMA scheme; however, it is not necessary. At each node,the schedule of each superframe is generally the same, except fordynamic behaviour in the network (e.g. mobile nodes moving in and out ofrange). The scheduling of beacons into slots can be static or dynamic.Static allocation, in which the schedule is known in advance by allnodes, is simpler but does not allow slot reuse in multi-hop networks.Dynamic allocation entails additional communication overhead, eithermutually among the nodes according to a distributed algorithm, orbetween a scheduling controller (e.g. the location server) and thenodes.

Coarse time synchronisation is required between all nodes for the TDMAscheme; however, this only needs to be within a fraction of the slotduration (e.g. one percent, or 10 μs for 1 ms slots), which is readilyachieved in nodes designed to measure TOA with high accuracy (typicallybetter than 1 ns). The synchronisation time reference is provided by oneof the nodes either by fixed allocation or selection by the nodesthemselves (the latter alternative providing robustness should the timereference node fail). This time synchronisation is too coarse to be ofany assistance for localisation.

TOA reception nodes are adapted to receive a beacon, convert it todigital form, and process it to measure with high resolution the TOA ofthe beacon (step 220 of the method 200). A TOA reception node alsopreferably uses wireless communication to transmit the TOA values to thelocation server (step 230 of the method 200). In the preferredembodiment, the TOA data is sent to the location server in the datafield 470 of the beacon format 450 shown in FIG. 4b . Thus 400 in FIG.4a equally well represents a TOA reception node according to thepreferred embodiment. However, there are greater requirements on theperformance of TOA reception nodes compared to beaconing nodes in twoways. Firstly, the processing capabilities required for measuring theTOA are substantially greater than that required for generation ofbeacons. Secondly, a TOA reception node should have a receiver withgreater sensitivity and linearity for high accuracy measurement of TOAthan is required just for data reception.

The measurement of the TOA (step 220) is preferably carried out by a TOAreception node according to the method described in the PCT patentapplication no. PCT/AU2009/000647. However, any technique for themeasurement of TOA may alternatively be used.

A location server 600 according to the preferred embodiment isillustrated in FIG. 6. The location server 600 comprises an analog radioreceiver 610, an analog to digital converter 620, and digital processingelectronics 630. The location server 600 processes the received datafrom the TOA reception nodes and uses this information to estimate thelocation of mobile nodes (step 240). The location server 600 may alsoperform other functions such as performing and/or reporting systemdiagnostics and recording and formatting sensor data from the system.The digital processing electronics 630, on which the location estimationand any other processing are implemented, are therefore more powerfulthan the digital processing electronics 430 of either an anchor node ora beacon node.

In one embodiment, the digital processing electronics 630 comprises thedigital processing electronics 430 of an anchor node connected via a USBinterface to a general purpose computer system 300 such as that shown inFIG. 3, wherein the processing of step 240 may be implemented assoftware, such as one or more application programs executable within thecomputer system 300. In particular, the processing of step 240 iseffected by instructions in the software that are carried out within thecomputer system 300. The instructions may be formed as one or more codemodules, each for performing one or more particular tasks. The softwaremay also be divided into two separate parts, in which a first part andthe corresponding code modules performs the location estimationprocessing and a second part and the corresponding code modules managean interface between the first part and other systems. The software maybe stored in a computer readable medium, including the storage devicesdescribed below, for example. The software is loaded into the computersystem 300 from the computer readable medium, and then executed by thecomputer system 300. A computer readable medium having such software orcomputer program recorded on it is a computer program product. The useof the computer program product in the computer system 300 preferablyeffects an advantageous apparatus for estimating the location of mobilenodes.

As seen in FIG. 3, the computer system 300 is formed by a computermodule 301, input devices such as a keyboard 302 and a mouse pointerdevice 303, and output devices including a printer 315, a display device314 and loudspeakers 317. An external Modulator-Demodulator (Modem)transceiver device 316 may be used by the computer module 301 forcommunicating to and from a communications network 320 via a connection321.

The computer module 301 typically includes at least one processor unit305, and a memory unit 306 for example formed from semiconductor randomaccess memory (RAM) and read only memory (ROM). The module 301 alsoincludes a number of input/output (I/O) interfaces including anaudio-video interface 307 that couples to the video display 314 andloudspeakers 317, an I/O interface 313 for the keyboard 302 and mouse303 and optionally a joystick (not illustrated), and an interface 308for the external modem 316 and printer 315. In some implementations, themodem 316 may be incorporated within the computer module 301, forexample within the interface 308. The computer module 301 also has alocal network interface 311 which, via a connection 323, permitscoupling of the computer system 300 to a local computer network 322,known as a Local Area Network (LAN). As also illustrated, the localnetwork 322 may also couple to the wide network 320 via a connection324, which would typically include a so-called “firewall” device orsimilar functionality. The interface 311 may be formed by an Ethernet™circuit card, a wireless Bluetooth™ or an IEEE 802.11 wirelessarrangement.

The interfaces 308 and 313 may afford both serial and parallelconnectivity, the former typically being implemented according to theUniversal Serial Bus (USB) standards and having corresponding USBconnectors (not illustrated). Storage devices 309 are provided andtypically include a hard disk drive (HDD) 310. Other devices such as afloppy disk drive, a flash memory drive, and a magnetic tape drive (notillustrated) may also be used. An optical disk drive 312 is typicallyprovided to act as a non-volatile source of data. Portable memorydevices, such optical disks (eg: CD-ROM, DVD), USB-RAM, and floppy disksfor example may then be used as appropriate sources of data to thesystem 300.

The components 305, to 313 of the computer module 301 typicallycommunicate via an interconnected bus 304 and in a manner which resultsin a conventional mode of operation of the computer system 300 known tothose in the relevant art. Examples of computers on which the describedarrangements can be practised include IBM-PC's and compatibles, SunSparcstations, Apple Mac™ or like computer systems evolved therefrom.

Typically, the application programs discussed above are resident on thehard disk drive 310 and read and controlled in execution by theprocessor 305. Intermediate storage of such programs and any datafetched from the networks 320 and 322 may be accomplished using thesemiconductor memory 306, possibly in concert with the hard disk drive310. In some instances, the application programs may be supplied to theuser encoded on one or more CD-ROM and read via the corresponding drive312, or alternatively may be read by the user from the networks 320 or322. Still further, the software can also be loaded into the computersystem 300 from other computer readable media. Computer readable mediarefers to any storage medium that participates in providing instructionsand/or data to the computer system 300 for execution and/or processing.Examples of such media include floppy disks, magnetic tape, CD-ROM, ahard disk drive, a ROM or integrated circuit, a magneto-optical disk, ora computer readable card such as a PCMCIA card and the like, whether ornot such devices are internal or external of the computer module 301.Examples of computer readable transmission media that may alsoparticipate in the provision of instructions and/or data include radioor infra-red transmission channels as well as a network connection toanother computer or networked device, and the Internet or Intranetsincluding e-mail transmissions and information recorded on Websites andthe like.

The second part of the application programs and the corresponding codemodules mentioned above may be executed to implement one or moregraphical user interfaces (GUIs) to be rendered or otherwise representedupon the display 314. Through manipulation of the keyboard 302 and themouse 303, a user of the computer system 300 and the application maymanipulate the interface to provide controlling commands and/or input tothe applications associated with the GUI(s).

The digital processing electronics 630 may alternatively be dedicatedhardware such as one or more integrated circuits performing thefunctions or sub functions of the step 240. Such dedicated hardware mayinclude graphic processors, digital signal processors, or one or moremicroprocessors and associated memories with data interfaces (e.g. WLANor USB or serial interface) but no user interface devices. The digitalprocessing electronics 430 of the beaconing/TOA reception node 400 isalso preferably dedicated hardware of this kind.

To perform the location estimation of step 240, the location server 600can utilise round trip or mobile transmit localisation, depending on thespecifics of the application. An advantage of mobile transmitlocalisation for tracking objects moving at high velocity is that thisapproach only uses a single beacon, and is thus only affected by motionfor the duration of the beacon (preferably about 0.5 ms). For round triplocalisation, the estimation requires all beacons to and from the mobilenode in a superframe, which may be extended over a significant period oftime (up to 100 ms where 20 slots of 5 ms are used). It is describedbelow how the effect of constant velocity motion can be corrected forunder round trip localisation. A tradeoff in the choice of thelocalisation algorithm is that round trip localisation results aredegraded by non-constant velocity motion over the superframe, whilemobile transmit localisation results are degraded by errors in anchornode time synchronisation.

Factors such as mobile node velocity and hardware constraints determinethe selection of the localisation algorithm. The location server 600 canimplement multiple localisation algorithms simultaneously, as in thefollowing exemplary scenarios:

-   -   The system may have more than one type of mobile node, one        capable of measurement of TOA in real time (TOA reception node)        and another not (beaconing node). The former type is more        accurate but is larger and has a shorter battery life. Both use        the same beacon format 450; however, the latter type does not        put the measured TOA values into the beacon data payload 470.        The location server detects from the received beacon whether the        mobile node is a TOA reception node or not, and selects either        round trip or mobile transmit localisation respectively.    -   A mobile node may not be capable of measuring TOA at the normal        update rate, due to constraints in processing capability, but        may be able to measure TOA at a reduced rate. In this case the        location server uses mobile transmit localisation, but        occasionally uses round trip localisation so that the        propagation delay of the mobile node can be determined.    -   A mobile node may both a beaconing node and a TOA reception        node, and with any change in data from the mobile node the        location server 600 can select whether to use round trip or        mobile transmit localisation. The selection could be made based        on estimated mobile velocity, or it could be based on an        estimate of the localisation accuracy for both algorithms as        determined by the location server.

The following sections describe in detail methods for localisation andtracking of mobile nodes based on round trip localisation and mobiletransmit localisation. FIG. 7 is a flow diagram illustrating a method700 according to the preferred embodiment of estimating the location ofmobile nodes. The main decisions in the method 700 are whether thepropagation delay of the anchor nodes is known from prior calibration,and whether mobile transmit or round trip localisation is used. In thecase of round trip localisation with known anchor node propagation delayvalues, there is the further choice of using a MMSE-based or POCS-basedlocalisation algorithm. These choices may be made dynamically, each timethe method 700 is executed, or in advance, in which case only therelevant portions of the method 700 need be implemented.

The steps of the method 700 are mostly carried out by the locationserver 600, except for TOA measurement steps 715, 752, 735, 770, and 775which are done by beaconing nodes and TOA reception nodes 400, and theresults sent to the location server 600, as shown by the method 200. Themethod 700 starts at step 710 where it is determined whether thepropagation delay of the anchor nodes is known from prior calibration.If not, the method 700 proceeds to step 715 at which the TOA at eachanchor node from all other anchor nodes is measured. In step 720 thecorrected round trip delay between each pair of anchor nodes is computedas described below. Step 725 follows, at which the propagation delay ateach anchor node is computed as described below. Next, it is checked atstep 730 whether round trip localisation is to be used. If not, step 735measures the TOA at each anchor node from each mobile node. Step 740follows, at which the anchor nodes are time synchronised as describedbelow. The Pseudo-Range (see below) between all anchor and mobile nodesis then computed at step 745 as described below, after which at step 750a robust MMSE-based Time Difference of Arrival (TDOA) algorithmdescribed below is used to estimate the location of each mobile node.The method 700 then concludes at step 795.

If round trip localisation is to be used in the case where anchor nodepropagation delays were not known from prior calibration (but wereinstead computed in steps 715 to 725), step 752 measures the TOA at eachanchor node from each mobile node, and vice versa. Then at step 754, themethod 700 computes the Corrected Round Trip Delay between each anchornode and each mobile node as described below. Step 756 follows, at whichthe Pseudo-Range between all anchor and mobile nodes is computed asdescribed below. Finally at step 758 a robust MMSE-based TOA algorithm,described below, is used to estimate the location of each mobile node.If the propagation delay at the mobile nodes is known, step 756 computesrange rather than pseudo-range, and step 758 would use either a robustMMSE-based or a POCS-based TOA algorithm, to be described below, toestimate the location of each mobile node from the computed ranges.However, the propagation delay at the mobile nodes is unlikely to beknown as the propagation delay of the anchor nodes was initiallyunknown. The method 700 then concludes at step 795.

In the case where the propagation delay of the anchor nodes is known,step 765 checks whether round trip localisation is to be used. If not,step 770 measures the TOA at each anchor node from all other anchornodes and all mobile nodes. The method 700 then continues from step 740as described above.

If round trip localisation is to be used, step 775 measures the TOA ateach anchor node from each mobile node, and vice versa. Then at step780, the method 700 computes the Corrected Round Trip Delay between eachanchor node and each mobile node as in step 754. Step 785 follows, atwhich the range between all anchor and mobile nodes is computed(assuming the propagation delay at the mobile nodes is known, which islikely since the propagation delay at the anchor nodes is known).Finally at step 790 the robust MMSE- or POCS-based TOA algorithm is usedto estimate the location of each mobile node, as in step 758. If thepropagation delay at the mobile nodes is unknown, step 785 computesPseudo-Range rather than range, and step 790 can only use the robustMMSE-based TOA algorithm, as in step 758. The method 700 then concludesat step 795.

Round Trip Localisation

Next, a method will be described for measurement of round trip delaybetween a pair of nodes, with correction for motion and frequencyoffset. This method is used at steps 720, 754, and 780 of the method700, and provides the basis for round trip localisation and computationof anchor node propagation delay (step 725).

The two nodes are labelled as M (typically, but not necessarily, amobile node) and B (an anchor node). Node M transmits a beacon first,followed by node B after a delay of τ_(MB) determined by the beaconschedule (see FIG. 5). After a delay of τ_(SF) (the superframe length),this sequence is repeated, as illustrated in FIG. 8a . The beacons aretransmitted at times t₁, t₃, t₅ and t₇, and received at times t₂, t₄, t₆and t₈. The difference between the transmit time and the receive time,e.g. t₂−t₁, is the sum of the propagation delay through the transmitterelectronics (Δ_(j) ^(tx), where i can be M or B), the propagation timethrough the air (d_(ij)/c where d_(ij) is distance between the twonodes, c is speed of light, and j can be B or M), and the propagationdelay through the receiver electronics (Δ_(j) ^(rx)).

The imperfections in the system are:

-   -   Time measurements are with respect to the local clock on the        respective nodes. The local clocks at the nodes are not time or        frequency synchronised, and this error can be modelled using the        relationship between true time t_(i) and the measured time at        node j, t_(i) ^(j), which is t_(i) ^(j)=α_(j)(t_(i)−t_(0,j)),        where α_(j) is the ratio of local clock frequency to true        frequency (close to unity, since temperature compensated crystal        oscillators are preferably used to set time that remain within 1        part per million of the true frequency) and t_(0,j) is the time        offset, i.e. the true time at which the local clock at node j        commences its count.    -   A node can only measure its own transmit and receive times, so        for example t₂ ^(M) does not exist.    -   The mobile node may be moving, with a significant displacement        occurring between the transmissions of the beacons from both        nodes. This is illustrated in FIG. 8b where M^(i) is the        location of the mobile node at time t_(i). It can be assumed        that the motion of the mobile node is negligible in the short        time interval between transmission (t₁) and reception (t₂) of a        beacon. In this diagram r_(ij) is a vector between nodes i and j        and d_(ij)=∥r_(ij)∥.

An estimate of the frequency difference between the pair of nodes can bemade at node M as follows:

$\begin{matrix}{{\begin{matrix}{D_{M} = \frac{\left( {t_{8}^{M} - t_{7}^{B}} \right) - \left( {t_{4}^{M} - t_{3}^{B}} \right)}{t_{8}^{M} - t_{4}^{M}}} \\{= {\left( {\alpha_{M} - \alpha_{B}} \right) + {\alpha_{A}\frac{d_{{BM}\; 7} - d_{{BM}\; 3}}{c\; \tau_{SF}}}}} \\{{\cong {\alpha_{MB} + \delta_{MB}}},}\end{matrix}\quad}{where}} & (1) \\{\delta_{MB} = {\frac{d_{{BM}\; 7} - d_{{BM}\; 3}}{c\; \tau_{SF}}.}} & (2)\end{matrix}$

α_(MB) is the frequency offset of the local clocks of the node pair, andδ_(MB) is the Doppler frequency shift due to the radial component of therelative motion between the node pair. An estimate of the frequencydifference at node B can likewise be made:

$\begin{matrix}{D_{B} = {\frac{\left( {t_{6}^{M} - t_{5}^{B}} \right) - \left( {t_{2}^{M} - t_{1}^{B}} \right)}{t_{6}^{M} - t_{2}^{M}} \cong {{- \alpha_{MB}} + {\delta_{MB}.}}}} & (3)\end{matrix}$

Note that using D_(M) and D_(B) the effects of frequency offset andrelative motion can be separated as follows:

$\alpha_{MB} = \frac{D_{M} - D_{B}}{2}$$\delta_{MB} = \frac{D_{M} + D_{B}}{2}$

Using the δ_(MB) terms between a mobile node and multiple anchor nodesit is possible to estimate the velocity of the mobile node withoutdetermining range or location.

The round trip delay measurement requires measurements in bothdirections between the pair of nodes. The uncorrected round trip delay,using the first pair of beacons in FIG. 8a , is:

$\begin{matrix}{T_{MB} = {\left( {t_{4}^{M} - t_{3}^{B}} \right) + \left( {t_{2}^{B} - t_{1}^{M}} \right)}} \\{= {{\tau_{MB}\left( {\alpha_{M} - \alpha_{B}} \right)} + {\alpha_{M}\left( {\Delta_{B}^{tx} + \Delta_{M}^{rx}} \right)} + {\alpha_{B}\left( {\Delta_{M}^{tx} + \Delta_{B}^{rx}} \right)} +}} \\{{{\alpha_{M}\frac{d_{{BM}\; 3}}{c}} + {\alpha_{B}\frac{d_{{BM}\; 1}}{c}}}} \\{\approx {{\tau_{MB}\alpha_{MB}} + \Delta_{M} + \Delta_{B} + {2\frac{d_{{BM}\; 1}}{c}} + \frac{d_{{BM}\; 3} - d_{{BM}\; 1}}{c}}}\end{matrix}\quad$

where Δ_(i)=Δ_(i) ^(tx)+Δ_(i) ^(rx). Assuming that relative velocitybetween the nodes is constant over the interval τ_(SF) (i.e. betweenmobile node locations M¹ and M⁵ in FIG. 8b ) and that the displacementover this interval is small relative to distance d_(BM), the last termmay be approximated as

${\frac{d_{{BM}\; 3} - d_{{BM}\; 1}}{c} \cong {\frac{\tau_{MB}}{\tau_{SF}} \cdot \frac{d_{{BM}\mspace{11mu} 7} - d_{{BM}\mspace{11mu} 3}}{c}}} = {\tau_{MB}{\delta_{MB}.}}$

Hence

$\begin{matrix}{\begin{matrix}{T_{MB} \cong {{\tau_{MB}\alpha_{MB}} + \Delta_{M} + \Delta_{B} + {2\frac{d_{{BM}\; 1}}{c}} + {\tau_{MB}\delta_{MB}}}} \\{= {{2\frac{d_{{BM}\; 1}}{c}} + \Delta_{M} + \Delta_{B} + {\tau_{MB}D_{M}}}}\end{matrix}\quad} & (4)\end{matrix}$

The quantity

$2\frac{d_{{BM}\; 1}}{c}$

is me corrected round trip delay. The quantities T_(MB) and D_(M)(equation (1)) are directly determined from the measured data, andτ_(MB) is known from the beacon TDMA schedule; if not, it can be readilyestimated from the TOA data as follows:

$\tau_{MB} \cong \frac{\left( {t_{4}^{M} + t_{3}^{B}} \right) - \left( {t_{2}^{B} + t_{1}^{M}} \right)}{2}$

The location of the mobile node (hence d_(BM1)) is unknown, and thepropagation delay Δ_(i) for each node may be unknown.

In round trip localisation (steps 758 and 790 of method 700), correctedround trip delay measurements are first made between anchor nodes andmobile nodes (steps 754 and 780). The use of round trip delaymeasurements for removing the requirement for time synchronisation iswell known, but using the corrected round trip delay computed as below,the effects of frequency offset and relative motion can also be removed.An important feature of this correction for motion and frequency offsetis that it is applied locally to each node pair, and no globalprocessing is required. Note that the motion is corrected to the time atwhich the mobile node transmits, hence all ranges between this mobilenode and multiple anchor nodes are corrected to the same time,compensating for the effect of constant velocity motion.

The propagation delay Δ_(B) of the anchor nodes is either known fromprior calibration or computed at step 725 using corrected round tripdelay measurements between anchor nodes as described below. Inlocalisation according to the present disclosure, round tripmeasurements between mobile nodes are not used, but these measurementsmay be used for other purposes, e.g. cooperative localisation.

If the propagation delay Δ_(M) of the mobile node is known, then fromequation (4) the corrected round trip delay

$2\frac{d_{{BM}\; 1}}{c}$

(step 780 or 754) is T_(MB)−Δ_(M)−Δ_(B)−τ_(MB)D_(M). The range betweenthe pair of nodes is therefore computed (step 785 or 756) as:

$\begin{matrix}{d_{BM} \cong {c \cdot {\frac{T_{MB} - \Delta_{M} - \Delta_{B} - {\tau_{MB}D_{M}}}{2}.}}} & (5)\end{matrix}$

From a set of such ranges (minimum 3 for 2D localisation or 4 for 3Dlocalisation) to anchor nodes at known locations, the location of themobile node is estimated (step 790 or 758).

If the propagation delay Δ_(M) of the mobile node is not known, thenfrom equation (4) the corrected round trip delay

${2\frac{d_{{BM}\; 1}}{c}} + \Delta_{M}$

(step 754 or 780) is T_(MB)−Δ_(B)−τ_(MB)D_(M). The pseudo-range betweenthe pair of nodes is therefore computed (step 756 or 785) as:

$\begin{matrix}{p_{BM} = {{d_{BM} + \frac{c\; \Delta_{M}}{2}} \cong {c \cdot {\frac{T_{MB} - \Delta_{B} - {\tau_{MB}D_{M}}}{2}.}}}} & (6)\end{matrix}$

All pseudo-ranges are offset from genuine ranges by a constant value ofcΔ_(M)/2; thus there is an extra unknown (Δ_(M)) that needs to be solvedfor in step 758 or 790. Therefore, the minimum number of pseudo-rangemeasurements is 4 for 2D localisation and 5 for 3D localisation. Thesolution is mathematically the same as Time Difference of Arrival (TDOA)localisation used at step 750 (which solves for an unknown transmittime), described below.

Three algorithms for round trip localisation are described below:

-   -   Robust Minimum Mean Square Error (MMSE) (step 758 and 790),        estimating mobile node location and mobile node propagation        delay from pseudo-range values. This is good for calibration of        mobile node propagation delay, but is typically not used in        multipath environments.    -   Robust Minimum Mean Square Error (step 790 and 758), estimating        mobile node location from range values with a known value of        mobile node propagation delay.    -   Projection onto Convex Sets (POCS) algorithm (step 790 and 758),        estimating mobile node location from range values with a known        value of mobile node propagation delay.

This works well when multipath causes a positive bias on many rangeestimates.

Pre-Filtering of Range Data

Pre-filtering of the range data improves localisation accuracy byeliminating bad measurements prior to the localisation steps 758 and790. Given multiple measurements of the range d_(BM) between an anchornode and a mobile node taken over a period of seconds, an improvedestimate of the true range at any given time can be determined by avariety of filtering and interpolation operations. Applying theseoperations prior to estimation of the node location using either thePOCS or MMSE approaches described below can result in improvedestimation accuracy. Because these operations act on the range databefore the localisation step, the result is quite different to applyinga filter (such as a Kalman filter or non-linear filter) to the estimatedlocations. The benefits of pre-filtering are:

-   -   Interpolation of missing range data. In some environments,        breakdown in the data communications may result in occasional        missing measurements. As a result, there may be an insufficient        number of ranges to estimate the location of the mobile node.        This can be overcome by interpolating or extrapolating the        missing range data from previous or subsequent measurements for        the anchor and mobile node pair.    -   Filtering of range data to reduce noise and/or remove bad        measurements.

Any of a number of filtering operations can be applied to the rangedata, taking into account a priori information about the characteristicsof the motion of the mobile node. Such filtering may include for examplelinear filters (e.g. low pass filter and Kalman filter) or non-linearfilters (e.g. median filter). In an indoor environment with strongmultipath propagation and many walls, the direct path is often lost,resulting in range estimates that are longer than the true range. Todeal with this situation, a nonlinear filter which replaces infeasiblemeasurements with a value extrapolated from past measurements can beused. One embodiment of such a filter limits the maximum difference inrange between the minimum range from of any of the previous 5superframes and the range from the current superframe.

The same filtering operations can be applied to pseudo-range databetween a given mobile node and anchor nodes, as the distance offsetbetween the pseudo-range and the (unknown) true range is the same foreach of these measurements.

Round Trip Localisation Using Robust MMSE

The MMSE cost function to estimate the mobile node location using therange measurements between a mobile node and K anchor nodes (step 758 or790) is

$\begin{matrix}{{\overset{\Cap}{x}}_{M} = {\arg \left\lbrack {\min\limits_{x_{M}}{\sum\limits_{i = 1}^{K}{w_{i}\left( {d_{iM} - {{x_{i} - {\overset{\Cap}{x}}_{M}}}} \right)}^{2}}} \right\rbrack}} & (7)\end{matrix}$

where w_(i) is an optional weight that is preferably inverselyproportional to the noise variance in the range measurement. Thelocations x_(i) of the anchor nodes are known.

In the case that the propagation delay of the mobile node is not known,the mobile node location and propagation delay are estimated from thepseudo-range measurements (step 758 or 790) as

$\begin{matrix}{{\overset{\Cap}{x}}_{M} = {\arg\left\lbrack {\min\limits_{x_{M},\Delta_{M}}{\sum\limits_{i = 1}^{K}{w_{i}\left( {p_{iM} - \frac{c\; \Delta_{M}}{2} - {{x_{i} - {\overset{\Cap}{x}}_{M}}}} \right)}^{2}}} \right\rbrack}} & (8)\end{matrix}$

Finding the minimising argument of either cost function is a non-linearproblem with many solution strategies. An initial linear solutionfollowed by one or more non-linear iterations using a Taylor expansion(usually less than five iterations are required) is preferable.

To make the solution more robust, bad range measurements (e.g. ones witha significant bias due to multipath) are preferably removed fromconsideration. An algorithm for doing this is given by the pseudocode inAppendix A. The location and the error in the location estimate arecomputed at line 5. If the error is less than a threshold, or the numberof ranges is less than or equal to a minimum number, the “repeat” loopat line 4 terminates. Each range or pseudo-range measurement is thenexcluded in turn at line 9, which recomputes the location and the errorin the location estimate with the remaining range or pseudo-rangemeasurements. After applying a small bias towards using moremeasurements (k is less than one, with 0.9 often a good choice) at line13, if the minimum such location error is smaller than the original,all-in error computed at line 5, then the ‘bad’ measurement is removed(line 14). The “repeat” loop at line 4 continues until no measurementsare removed in an iteration (line 16).

The location error estimate is computed as the product of an estimate ofthe range error and the GDOP (geometric dilution of precision) and isgiven by:

$\begin{matrix}{{\hat{E}}_{M} = {{GDOP} \cdot {\sqrt{\frac{\sum\limits_{i = 1}^{K}\left( {d_{iM} - {{x_{i} - {\overset{\Cap}{x}}_{M}}}} \right)^{2}}{K - 2}}.}}} & (9)\end{matrix}$

Where the pseudo-range is measured,

$d_{iM} = {p_{iM} - \frac{c\; \Delta_{M}}{2}}$

using the computed value of Δ_(M). Equation (9) is based on thesimplifying assumption that the noise in the range (or pseudo-range)measurements is independent and identically distributed, which while notstrictly true has been found to work very well with real data. The GDOPis calculated as a Cramer-Rao lower bound (see e.g. Larsson, E. G.,“Cramer-Rao bound analysis of distributed positioning in sensornetworks,” IEEE Signal Processing Letters, vol. 11, no. 3, pp. 334-337,March 2004). This calculation depends upon the location of the anchornodes, and whether or not the mobile node propagation delay is beingestimated.

Round Trip Localisation Using POCS

The other round-trip localisation approach is the Projection Onto ConvexSets (POCS) algorithm (step 758 or 790), where each constraint set is acircle centred on an anchor node with the radius given by the estimatedrange to that anchor node. The POCS algorithm may be extended to 3dimensional locations by taking the constraint sets as spheres ratherthan circles. Unlike the MMSE algorithm, which penalises mobile nodelocations quadratically for their distance from the estimated range, thePOCS algorithm applies no penalty for the range to the mobile node beingless than or equal to the estimated range. As a result, the POCSalgorithm gives good results when large positive errors are likely, suchas in indoor environments where the direct path may be severelyattenuated by intervening walls.

A point in the intersection of the constraint sets is found by aniterative process, illustrated in FIG. 9. Constraints sets for threeanchor nodes labelled B1, B2 and B3 are shown as circles centred at eachanchor node, with radii equal to the respective ranges from each anchornode. A random starting point, e.g. 900 or 910, is updated by projectingonto each of the constraint sets in turn. After a small number ofiterations (generally less than 10), the point will be in the (shaded)intersection region 920 of the constraint sets. The end point of thepath is recorded. The path 915 is taken by the starting point 910 as itis projected onto the constraint sets associated with B1, B2 and B3 inturn. A second path 905 is taken by a starting point 900 as it isprojected onto the sets associated with B3, B1 and B2 in turn.

The intersection of the constraint sets may be empty. This can bedetected by determining whether the end point is not inside all theconstraint sets after a substantial number of iterations (preferably20). There are several possible ways of dealing with this case. In oneapproach, the ranges to one or more of the anchor nodes are increased bya small amount and the constraint set intersection is recomputed. Thisis repeated until the intersection of the constraint sets is non-empty.In an alternative approach, a number of different starting points arechosen, and the POCS algorithm is run for a fixed number of iterationsfor each starting point, and the resulting end points are averaged. Inyet another approach, only a single starting point is used, and thesolution point is given by the average of the end points over a numberof steps of the iterative algorithm.

Just as the intersection of the constraint sets may be empty, it mayalso be very large, indicated by determining whether multiple end pointsare widely dispersed. This can be dealt with using strategies similar tothose for the case of an empty intersection discussed above. In oneapproach, the range to at least one of the anchor nodes is decreased andthe POCS algorithm run again. This is repeated until the intersectionregion shrinks to a small size. Alternatively, the end point formultiple different starting points may be averaged to estimate thecentroid of the constraint set intersection region. In FIG. 9, the endpoint for two different starting points is shown. Taking the median ofseveral such end points gives a point near the centroid of the shadedintersection region. The median is the location estimate for the mobilenode.

Mobile Transmit Localisation

In mobile transmit localisation (step 750), the location of a mobilenode is estimated based on a single beacon from the mobile node to eachanchor node. This requires time synchronisation of the anchor nodes(step 740) at the time at which the beacon is sent. If the propagationdelay of the mobile node is known, it is possible to time synchronisethe mobile node to the other nodes and what is generally called a TOAlocalisation algorithm may be used. However, when the mobile node is notalso a TOA reception node, it is not possible to separate the effects ofclock time offset and propagation delay, and if propagation delay is notknown time synchronisation of the mobile node is impossible, in whichcase a Time Difference Of Arrival (TDOA) algorithm can be used toestimate the mobile node location. Even if time synchronisation of themobile node is possible, the TDOA algorithm is preferred in step 750 toavoid this synchronisation step.

If the mobile node is time synchronised, given the transmit time fromthe mobile t_(M) and a receive time at each anchor node/of t_(rx,i) themeasured range between the node pairs is given by

d _(iM) =c(t _(rx,i) −t _(M)−Δ_(M) ^(tx)−Δ_(i) ^(rx)).  (10)

A set of such measurements can be used as input for the robust MMSEalgorithm based on range described above with reference to equation (7).Note that it is not usually convenient to calculate the separatetransmit and receive delays, so this localisation algorithm ispreferably not used.

Not using the transmit time from the mobile node simplifies the problem,as the mobile node does not need to be time synchronised to the anchornodes, nor is any propagation delay information for the mobile nodeneeded. The measured pseudo-range (step 745) is

p _(iM) =d _(iM) +c(t _(M)+Δ_(M) ^(tx) =c(t _(rx,i)−Δ_(i) ^(rx)).  (11)

A set of such measurements can be used as input for the robust MMSE TDOAalgorithm based on pseudo-range described above with reference toequation (8), except where above the unknown range offset was cΔ_(M)/2,in this case it is c(t_(M)+Δ_(M) ^(tx)).

Propagation Delay at Anchor Nodes

The propagation delay of anchor nodes at known locations can be readilycomputed (step 725) using the corrected round trip delay

$2\frac{d_{ij}}{c}$

between anchor nodes calculated at step 720. In equation (4), thedistance between the anchor nodes i and j is known, as are τ_(ij) andD_(i) using equation (1), so the only unknowns are the propagationdelays of the two anchor nodes. For each measurement between anchornodes i and j, equation (4) may be rewritten as

T _(ij)−2d _(ij) /c−τ _(ij) D _(i)=Δ_(i)+Δ_(j)  (13)

where the terms on the left side are known. This can be written as a setof linear equations in the form AΔ=b where Δ is a column vector of Δ_(i)values and b is a column vector of the terms on the left side ofequation (13). There are generally more measurements than unknowns, sothe system is overdetermined, and the least squares solution is:

Δ=(A ^(T) A)⁻¹ A ^(T) b.  (14)

Anchor Node Synchronisation

The time offset between anchor nodes is continually changing due to theoffset in node clock frequencies (which themselves vary over time).Hence, for the calculation of mobile node location using TDOA, the timeoffset between the anchor nodes needs to be determined at the time thatthe mobile node transmitted its beacon (step 740). Assume that anchornode i transmits a beacon at t₁ that is received by anchor node j at t₂.The difference between the measured receive and transmit times at timet₁ is

$\begin{matrix}{{t_{2}^{j} - t_{1}^{i}} = {{\alpha_{j}\left( {{d_{ij}/c} + \Delta_{i}^{tx} + \Delta_{j}^{rx} - t_{0,j}} \right)} + {\alpha_{i}t_{0,i}}}} \\{\approx {t_{0,i} - t_{0,j} + {d_{ij}/c} + \Delta_{i}^{tx} + {\Delta_{j}^{rx}.}}}\end{matrix}\quad$

The error in this approximation is insignificant. d_(u) is known as theanchor node locations are known, and Δ_(i) ^(tx) and Δ_(j) ^(rx) can besolved for, but are actually known from previous calibration or separateanchor node propagation delay calculation (step 725).

This difference needs to be adjusted to the time that the mobile nodetransmits, which is offset from t₁ by τ_(iM). It is assumed that thefrequency offset is constant over this small time interval, henceshifting t=0 to the time at which the mobile node transmits yields

$\begin{matrix}{{t_{0,i} - t_{0,j}} \approx {t_{2}^{j} - t_{1}^{i} - {d_{ij}/c} - \frac{\Delta_{i} + \Delta_{j}}{2} - {\alpha_{ij}{\tau_{iM}.}}}} & (14)\end{matrix}$

This forms a generally overdetermined linear set of equations that canbe solved for the time offsets t_(0,i) by arbitrarily setting one of thenodes to have zero offset and finding the least squares solution.

The value τ^(iM) can be measured using the receive time of the beaconfrom the mobile node at node i, however a more robust measurement is toform a least squares estimate of all beacon transmit times over allmeasurements in a superframe.

Variations

-   -   Two way ranging with correction for motion, frequency offsets        between nodes and node propagation delay is useful in        applications without also performing localisation (e.g. in        underground mines).    -   Gating of data to remove measurements inconsistent with expected        location or range.    -   Use of temporal filter (e.g. Kalman or particle filter) to        reduce noise in mobile location.    -   Perform localisation using filter with input range or        pseudo-range, not location.    -   Data fusion with other aiding sources (INS, GPS etc) to improve        results.

It is apparent from the above that the arrangements described areapplicable to the wireless localisation industries.

The foregoing describes only some embodiments of the present invention,and modifications and/or changes can be made thereto without departingfrom the scope and spirit of the invention, the embodiments beingillustrative and not restrictive.

APPENDIX A For each mobile node M Repeat Compute Mobile Node Location 

 _(M) and Location Error Estimate 

 _(M) If 

 _(M) less than threshold or number of ranges less than or equal tothreshold Break (location of M is 

 _(M) , go to next iteration of outer for loop) For each anchor node iCompute Mobile Node Location 

 _(M / i) and Location Error Estimate 

 _(M / i) after removing measurement d_(iM) or p_(iM) Keep track ofresult (i_(min) , 

 _(M / i) _(min) and 

 _(M / i) _(min) ) with lowest location error estimate If 

 _(M / i) _(min) < k 

 _(M) Remove measurement d_(i) _(min) _(M) from further consideration asbad Else Break (location of mobile M is 

 _(M) , go to next iteration of outer for loop)

1. A method of estimating a location of a mobile node using anchornodes, the method comprising: broadcasting beacons by nodes includingsaid mobile node and said anchor nodes, wherein said mobile node andsaid anchor nodes broadcast the respective beacon at least once in asuperframe; measuring transmit times of the beacons; measuring atime-of-arrival of each respective beacon at each of said mobile nodeand said anchor nodes receiving each respective beacon; calculatingparameter offsets between the nodes based on the beacons transmitted intwo or more superframes, the measured transmit times of the beacons, andthe measured times-of-arrival of the beacons; calculating a plurality ofround trip delays based on the calculated parameter offsets, themeasured transmit times, and the measured times-of-arrival; andestimating the location of said mobile node relative to said anchornodes using said calculated plurality of round trip delays.
 2. Themethod according to claim 1, wherein the parameter offsets compriserelative frequency offsets and relative doppler shifts.
 3. The methodaccording to claim 1, wherein the broadcasting of the beacons isscheduled using the superframe.
 4. The method according to claim 1,wherein the broadcasting is performed using a 802.11 standard.
 5. Themethod according to claim 1, further comprising: correcting said roundtrip delays for propagation delays at said anchor nodes and said mobilenode; and computing ranges between said nodes based on the correctedround trip delays, wherein the computed ranges are used to estimate thelocation of the mobile node.
 6. The method according to claim 1, furthercomprising: computing ranges between said nodes based on corrected roundtrip delays, wherein the computed ranges are used to estimate thelocation of the mobile node.
 7. The method according to claim 5, whereinthe propagation delays are determined from prior calibration orcalculated using the corrected round trip delays between said anchornodes.
 8. The method according to claim 5, further comprising:pre-filtering the computed ranges between said anchor nodes and saidmobile node.
 9. The method according to claim 8, wherein saidpre-filtering comprises any one of: interpolating or extrapolatingmissing range data from the computed ranges; and filtering the computedranges to reduce noise and/or remove bad measurements.
 10. The methodaccording to claim 9, wherein said filtering comprises linear ornon-linear filters.
 11. The method according to claim 6, wherein thestep of estimating the location of said mobile node relative to saidanchor nodes comprises the sub-steps of: estimating locations of saidmobile node and corresponding errors in respective said locationestimates, wherein each estimated location is determined from a subsetof the computed ranges, and wherein each subset of the computed rangesexcludes one range from the set of computed ranges; discarding each ofthe computed ranges whose exclusion gave an error estimate that is lessthan a threshold; and estimating the location of said mobile node fromundiscarded computed ranges, the undiscarded computed ranges being thoseof the computed ranges that have not been discarded.
 12. The methodaccording to claim 11, wherein said threshold is an error estimate of alocation estimate determined from all of the computed ranges.
 13. Themethod according to claim 11, wherein said estimating sub-step comprisesminimising a weighted sum over said anchor nodes of a squared differencebetween each computed range and a distance between a candidate locationand the location of a corresponding anchor node.
 14. The methodaccording to claim 11, wherein each of said error estimates in theestimated locations comprises an estimate of a computed range error anda term relating the computed range error to said error in the estimatedlocation.
 15. The method according to claim 11, wherein the discardingof the computed ranges is performed until a number of the undiscardedcomputed ranges reaches a minimum number.